TY - GEN
T1 - Design Method of Analog Sigmoid Function and its Approximate Derivative
AU - Chabane, Lylia Thiziri
AU - Pham, Dang Kien Germain
AU - Chollet, Paul
AU - Desgreys, Patricia
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - In this paper, we propose to implement the sigmoid function, which will serve as an activation function of the neurons of a Multi Layer Perceptron (MLP) network, as well as its approximate derivative using an analog circuit. Several implementations have already been proposed in the literature, in particular, by Lu et al. (2000), which offers both a configurable and simple circuit realized in 1.2μm technology. In this paper we demonstrate the circuit design of a sigmoid function based on Lu et al. using 65 nm technology in order to reduce energy consumption and circuit area. The design is based on an in-depth theoretical analysis of the circuit and validated by circuit level simulations. The main contributions of the paper are a modification of topology of the circuit in order to meet the required nonlinear response of the circuit and the extraction of the DC power consumption of the resulting circuit.
AB - In this paper, we propose to implement the sigmoid function, which will serve as an activation function of the neurons of a Multi Layer Perceptron (MLP) network, as well as its approximate derivative using an analog circuit. Several implementations have already been proposed in the literature, in particular, by Lu et al. (2000), which offers both a configurable and simple circuit realized in 1.2μm technology. In this paper we demonstrate the circuit design of a sigmoid function based on Lu et al. using 65 nm technology in order to reduce energy consumption and circuit area. The design is based on an in-depth theoretical analysis of the circuit and validated by circuit level simulations. The main contributions of the paper are a modification of topology of the circuit in order to meet the required nonlinear response of the circuit and the extraction of the DC power consumption of the resulting circuit.
KW - Activation function
KW - analog CMOS circuit
KW - approximate derivative
KW - backpropagation
KW - multi-layer perceptron
KW - sigmoid function
U2 - 10.1109/DCIS53048.2021.9666181
DO - 10.1109/DCIS53048.2021.9666181
M3 - Conference contribution
AN - SCOPUS:85124993050
T3 - 36th Conference on Design of Circuits and Integrated Systems, DCIS 2021
BT - 36th Conference on Design of Circuits and Integrated Systems, DCIS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th Conference on Design of Circuits and Integrated Systems, DCIS 2021
Y2 - 24 November 2021 through 26 November 2021
ER -
